TY - GEN
T1 - The wisdom of the gaming crowd
AU - Jeffrey, Robert
AU - Bian, Pengze
AU - Ji, Fan
AU - Sweetser, Penny
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/11/2
Y1 - 2020/11/2
N2 - In this paper, we report on three projects in which we are applying natural language processing techniques to analyse video game reviews. We present our process, techniques, and progress for extracting and analysing player reviews from the gaming platform Steam. Analysing video game reviews presents great opportunity to assist players to choose games to buy, to help developers to improve their games, and to aid researchers in further understanding player experience in video games. With limited previous research that specifically focuses on game reviews, we aim to provide a baseline for future research to tackle some of the key challenges. Our work shows promise for using natural language processing techniques to automatically identify features, sentiment, and spam in video game reviews on the Steam platform.
AB - In this paper, we report on three projects in which we are applying natural language processing techniques to analyse video game reviews. We present our process, techniques, and progress for extracting and analysing player reviews from the gaming platform Steam. Analysing video game reviews presents great opportunity to assist players to choose games to buy, to help developers to improve their games, and to aid researchers in further understanding player experience in video games. With limited previous research that specifically focuses on game reviews, we aim to provide a baseline for future research to tackle some of the key challenges. Our work shows promise for using natural language processing techniques to automatically identify features, sentiment, and spam in video game reviews on the Steam platform.
KW - Game reviews
KW - Natural language processing
KW - Nlp
KW - Qualitative analysis
KW - Steam
KW - Text mining
KW - Video games
UR - http://www.scopus.com/inward/record.url?scp=85096772084&partnerID=8YFLogxK
U2 - 10.1145/3383668.3419915
DO - 10.1145/3383668.3419915
M3 - Conference contribution
AN - SCOPUS:85096772084
T3 - CHI PLAY 2020 - Extended Abstracts of the 2020 Annual Symposium on Computer-Human Interaction in Play
SP - 272
EP - 276
BT - CHI PLAY 2020 - Extended Abstracts of the 2020 Annual Symposium on Computer-Human Interaction in Play
PB - Association for Computing Machinery, Inc
T2 - 7th ACM SIGCHI Annual Symposium on Computer-Human Interaction in Play, CHI PLAY 2020
Y2 - 2 November 2020 through 4 November 2020
ER -